INTRODUCTION:

The chronic hyperglycemia in diabetes is routinely treated with a range of antidiabetic drugs that have diverse mechanisms of action, such as stimulation of insulin secretion, decrease in insulin resistance, regulation of gluconeogenesis, glycogenesis, glycogenolysis, augmented glucose utilization and decrease in the absorption of glucose in the intestine¹. However, treatment with insulin injection forms the cornerstone for the treatment of both T1DM and T2DM and its frequency and success in pharmacotherapy vary in different ethnic subgroups². Most of the currently prescribed drugs for the treatment of diabetes often elicit detrimental side effects in addition to the development of resistance after extended use, hence search for novel drugs, preferably of plant origin continues³.

Avicularin is a bioactive flavonol originally isolated from the leaves of Polygonum aviculare Linn., commonly known as knotweed⁴. The herb is widely used in the traditional medicine of all cultures. Avicularin is a quercetin derivative in which the-L- arabinofuranosyl residue is linked at position 3 of quercetin via a glycosidic linkage. Avicularin is non-toxic and reported to possess a wide range of pharmacological properties, including antidiabetic, antioxidative, anticancer, anti-inflammatory, anti- arthritic and hepatoprotective⁵. More strikingly, it is capable of reversing multidrug resistance in human gastric cancer.The pharmacokinetic studies evidenced that the oral administration of Avicularin is absorbed swiftly and the peak plasma concentration reaches within 30min. and the concentration remained for more than four hours⁶. The urinary excretion of Avicularin was found to be77%. Recently, we have reported the antidiabetic properties of Avicularin in high fat diet fed –low dose STZ induced experimental type 2 diabetes inrats⁷.

The use of computational methods forms the elemental part of drug discovery. Protein–ligand docking and virtual screenings are the extensively used techniques that continue to demonstrate certification in strike identification and consequentoptimization⁸. They are also considered as reliable tools for drug repositioning to improve stability and efficacy. Moreover, these methods are reliable, reproducible, effective, swift, and facilitate the researchers to evaluate large virtual databases of molecular compounds as a first attempt to pave the way for the selection of more limited sets of compounds for detailed study⁹.

Molecular docking is an important technique employed for anticipating and investigating the binding capacity between protein targets and drugs. It offers detailed information about the functional groups present in the drug molecules with which the receptor interacts and creates a new coherent approach to drug design¹⁰. It made possible the visualization of the potential interactions between a ligand and its target. Its use for small peptides and other larger biomolecules has only been under development in the last decade¹¹. However, docking still faces difficulties, particularly regarding the correct modeling of ligand and protein flexibility, water-mediated interactions, and ligand-target interactions to accomplish an optimal complement of steric and physicochemical properties^12.

Glucokinase (EC 2.7.1.1; hexokinase IV or D) catalyses the phosphorylation of glucose to generate energy in the form of ATP. It has anaffinity for glucose that is within the physiological range of plasma glucose (half-saturation constant) of ∼7mM. The release of insulin from the β-cells of the pancreas is firmly correlates with the activity of GK and hence it is often termed the glucose sensor. The glucose sensor concept is reinforced by the fact that mutations in the GK gene can cause hyperglycemia as a result of ‘loss-of-function’ mutations or hypoglycemia through ‘gain-of-function’ mutations¹³. GK is therefore a crucial determinant of regulated insulin levels. Additionally, GK controls the glucose disposal in the liver that promotes glycogen and triglyceride synthesis. The inhibitory protein; glucokinase regulatory protein (GKRP) regulates the activity of GK. At basal glucose concentrations (5mmol/l), GKRP binds to GK with high affinity. Blood glucose homeostasis is maintained by the liver through glucose production via glycogenolysis from glycogen and gluconeogenesis from lactate and other gluconeogenic substrates¹⁴. During the postprandial state, hyperglycemia causes dissociation of GK from GKRP and translocation of GK into the cytoplasm; this results in increased glucose phosphorylation to Glucose-6-phosphate and conversion to glycogen, lactate, and triglyceride¹⁵.

Matschinsky and Wilson (2019)¹⁶ ascertained the major impact of GK on the control of systemic blood glucose homeostasis, which was summarized as the glucokinase glucose sensor paradigm. Studies on the physiological, biochemical, and molecular studies of insulin synthesis and secretion have shown that the activity of glucokinase and its task in glucose metabolism play a central role in regulating glucose-stimulated insulin secretion, consistent with the fuel hypothesis for insulin secretion. As a key target gene for diabetes mellitus, pharmacological activation of GK is considered a promising novel strategy for antihyperglycemic drug therapy¹⁷.

Aldose reductase (EC: 1.1.1.21; alcohol: NADPHoxidoreductase, ALR2) belongs to the aldo-ketoreductase (AKR) super family, and most of the AKR super family proteins are involved in the detoxification processes as they catalyze the reduction of a wide variety of substrates such as aliphatic and aromatic aldehydes, monosaccharides, steroids, polycyclic aromatic hydrocarbons and isoflavonoids. Human ALR2, encoded by AKR1B1gene, is a monomeric protein of 315 amino acids with a molecular mass of about 36kDa. Aldose reductase was described in 1956 by Hers as a glucose- reducing activity enzyme¹⁸. ALR2 is the first enzyme of the polyol pathway that catalyzes the reduction of glucose to sorbitol during chronic hyperglycemia, utilizing NADPH as a cofactor. The intracellular accumulation of sorbitol, due to increased aldose reductase activity during persistent hyperglycemia, such as those occurring in chronic diabetes, has been implicated in the development of various secondary complications of diabetes, especially retinopathy and the subsequent onset of cataract, which are practically not controlled by insulin treatment successfully¹⁹.

Aldosereductase inhibitors (ARIs) can prevent the reduction of glucose to sorbitol and avert complications of diabetes. Increasing evidences support that AR may play a critical role in the pathogenesis of a number of diabetic complications. Osmotic stress associated with sorbitol deposition and redox imbalance after depletion of NAD⁺and NADPH contributes to cell damage, resulting in cataract formation, neuropathy, and other diabetic complications²⁰. VanHeyningen(1959)²¹ reported that high levels of AR activity are present in the rat lens during diabetic and galactosemic cataractogenesis, AR-derived polyol-sorbitol and galactitol-accumulate in the ocular lens. Building on this observation, Varma and Kinoshita (1976)²² demonstrated that treatment with pharmacological inhibitors of AR ameliorates cataractogenesis in diabetic rats and galactose-exposed rabbits. Based on these observations, it was proposed that the accumulation of sorbitol in the lens, due to the AR- catalyzed reduction of glucose, causes osmotic swelling, resulting in ionic imbalance and protein insolubilization leading to cataractogenesis²³. A similar sequence of events could also account for the hyperglycemic injury associated with diabetic retinopathy, nephropathy, and neuropathy.

The Insulin Receptor (IR) is a heterotetramer formed by two extracellular α subunits and two transmembrane β subunits linked by disulfide bridges. The β chain with 194 residues forms the extracellular portion, and a single chain of 403 residues of the β chain constitutes the cytoplasmic domain are responsible for the receptor’s tyrosine kinase activity. Similar to insulin, the two IR chains are derived from the same precursor, the proreceptor, which is assembled after a proteolytic breakdown²⁴. The binding of insulin to the subunit of IR causes conformational changes in the receptor, leading to the activation of the tyrosinekinase-β subunit. The activated IR has the ability to autophosphorylate and phosphorylate intracellular substrates that are essential for initiating other cellular responses to insulin. These events eventually lead to the activation of downstream signaling molecules that participate in the insulin signaling pathway. Insulin signaling, including activation of IR tyrosinekinase activity, is impaired in most patients with diabetes mellitus²⁵. This resistance to insulin then leads to hyperglycemia and other metabolic abnormalities of the disease. Hence, compounds that augment insulin receptor tyrosine kinase activity would be useful in the treatment of diabetes mellitus.

In view of the beneficial and pharmacological properties bestowed with Avicularin and the clinical importance of glucokinase, aldose reductase and insulin receptor in the regulation of carbohydrate metabolism, in the present study an attempt has been made to study the interaction between Avicularin and the above targets to promote Avicularin as a potential candidate for the treatment of diabetes and its secondary complications.

MATERIALS AND METHODS:

Ligand preparation:

The phytochemical, Avicularin (quercetin-3-O-α-L- arabinofuranoside) is considered as the ligand molecule and its three-dimensional structure was constructed using Chemsketch and then converted into PDB file format by adding the hydrogen bonds (Fig.1). The Chemical formula of Avicularin is C₂₀H₁₈O₁₁ and its Molar mass is 434.35g/mol.

Fig. 1: The chemical structure of the Avicularin ligand.

Preparation of receptor protein:

The crystal structures of glucokinase, aldose reductase and insulin receptor were retrieved from RCSB-PDB (Research Collaboratory for Structural Bioinformatics Protein Data Bank). The preparation of glucokinase, aldose reductase and insulin receptor with the Auto Dock Tools involves the addition of hydrogen atoms to the target enzymes for protein docking simulation.

Molecular docking using Auto Dock:

Auto Dock Tools was used to study the docking simulations²⁶. Auto Dock 4.1 is used to study the molecular interactions between the Avicularin and enzyme receptors. AutoDock requires pre-calculated gridmaps, one for each type of atom present in the flexible molecules being docked, and stores the potential energy arising from the interaction with rigid macromolecules. This grid must surround the region of interest in the rigid macromolecule. Thesize of the grid box was set at 126, 126, and 126 Å (x, y, and z) to include all the amino acid residues that are present in rigid macromolecules. The AutoGrid 4.1Program, supplied with AutoDock4.1 program was used to produce gridmaps. The spacing between grid points was 0.375angstroms. AutoDock offers a variety of search algorithms to explore a given docking problem.

In the present study, the Lamarckian Genetic Algorithm (LGA) was chosen to search for the best conformers. During the docking process, a maximum of 10conformers were considered. The population size was set at 150, and the individuals were initialized randomly. The maximum number of energy evaluations was set to 500000, the maximum number of generations was 1000, the maximum number of top individuals that automatically survived was set to 1, the mutation rate was 0.02, and the crossover rate was 0.8. Step sizes were 0.2 Å for translations, 5.0° for quaternions and 5.0° for torsions. Cluster tolerance 0.5 Å, external grid energy 1000.0, max initial energy 0.0, max number of retries 10000, and 10 LGA runs were performed.

Auto Dock results were analyzed to study the interactions and the binding energy of the docked structure. It was run several times to get various docked conformations and to analyze predicted docking energy. The best ligand-receptor structure from the docked structures was chosen based on the lowest energy and minimal solvent accessibility of the ligand. The docking results were visualized using the Accelrys Visualizer Discovery studio tool.

RESULTS AND DISCUSSION:

Docking analysis:

Avicularin was allowed to bind at the active site of the enzyme glucokinase, and docking was performed at 50 different conformations. The docking conformation of Avicularin shows a low binding energy of – 8.26 Kcal/Mol with glucokinase. The docking of Avicularin into the active site of the glucokinase is visualized in Pymol (Fig.2).

Fig.2: Molecular interactions showing the binding sites of Glucokinase with Avicularin.

The hydroxyl group of Avicularin forms hydrogen bonds with the amino acids ASP 158, GLU67,ARG63, and LEU451at the active site of the enzyme, and the length of the hydrogen bond was measured. Docking energy and hydrogen bond interactions are shown inTable-1.

Table 1: Docking energy for Avicularin with Glucokinase

GLUCOKINASE
Gluco kinase Residue	Atom	Avicularin	Distance (Å)	Docking Energy (Kcal/Mol)
ASP158	OH	O	3.3	-8.26
GLU67	OH	N	3.1
ARG63	OH	O	2.7
LEU451	OH	O	3.2

Avicularin was allowed to bind at the active site of the enzyme aldose reductase, and docking was performed at 50 different conformations. The docking conformation of Avicularin shows a low binding energy of – 8.68 Kcal/Mol with aldose reductase. The docking of Avicularin into the active site of the aldose reductase was visualized in Pymol (Figure 3).

Fig. 3. Molecular interactions showing the binding sites of aldose reductase with Avicularin.

The hydroxyl group of Avicularin forms hydrogen bonds with the amino acids TRP111, HIS110, and TRP20 at the active site of the enzyme, and the length of the hydrogen bond was measured. Docking energy and hydrogen bond interactions are shown in Table-2.

Table 2: Docking energy for Avicularin with Aldose reductase.

Aldose reductase
Residue	Atom	Avicularin	Distance (Å)	Docking Energy (Kcal/Mol)
TRP111	NH	O	2.8	-8.68
HIS110	OH	N	3.0
TRP20	OH	N	2.9

Avicularin was allowed to bind at the active site of the insulin receptor and docking was performed at 50 different conformations. The docking conformation of Avicularin shows a low binding energy of–7.52Kcal/Mol with insulin receptor. The docking of Avicularin into the active site of the insulin receptor was visualized in Pymol (Figure4).

Fig. 4: Molecular interactions showing the binding sites of the insulin receptor with Avicularin.

The hydroxyl group of Avicularin forms hydrogen bond with the amino acid GLY1005, ASP1083, MET1079 and GLU1077 and TRP20 at the active site of the insulin receptor and the length of the hydrogen bond was measured. Docking energy and hydrogen bond interactions are shown in theTable-3.

Table 3: Docking energy for Avicularin with the Insulin receptor

Insulin receptor
Insulin receptor	Atom	Avicularin	Distance(Å)	Docking Energy (Kcal/Mol)
GLY1005	OH	N	2.6	-7.52
ASP1083	OH	O	2.8
MET1079	OH	O	2.8
GLU1077	OH	O	2.9

The chemical structure of the phytochemical ligand is presented in figure 1. The in silico interaction between Avicularin and the target proteins namely, glucokinase, aldose reductase and insulin receptor was depicted as Figures 2, 3, and 4 respectively and the data obtained for binding energy is presented as table 1, 2 and 3 respectively. The amino acids responsible for the binding of glucokinase with the Avicularin were identified as ASP158, GLU67, ARG63, and LEU451. The amino acids present in the active site of aldose reductase capable of interacting with Avicularin was found to be TRP111, HIS110, and TRP20. The binding of insulin receptor with the ligand Avicularin was identified as GLY1005, ASP108, MET1079 and, GLU1077 respectively. In docking studies, if a compound shows relatively less binding energy, it implies that the test compound has higher activity. The binding energy of the ligand for the target proteins was found to be –8.26, –8.68, and 7.52 for respectively. Several reports are available in the literature regarding the aldose reductase inhibitory activity of various phytochemicals derived from medicinal plants. Further studies are in progress to evaluate, through both in vitro and in vivo studies to assess the modulatory effects of Avicularinin the maintenance of normoglycemia in experimental diabetes. Further, the results of the in silico findings provide substantial evidence to show that Avicularin, thelead molecule, is capable of reducing intracellular sorbitol accumulation, which has been primarily implicated in the pathogenesis of late-onset diabetic complications like retinopathy, neuropathy and nephropathy. Further studies are in progress to evaluate the effect of Avicularinon other relevant receptors involved in the secondary complications of diabetes mellitus.

In silico docking study was carried out to identify the inhibiting potential of Avicularin against the aldose reductase enzyme. Lead optimization was achieved by computing of drug likeness properties. The drug likeness scores of Avicularinwere evaluated with the help of Lipinski’s rule. The docking studies were performed by AutoDock4.1. In the docking studies, if a lead molecule shows less binding energy compared to the standard, it demonstrates that the lead molecule has higher activity.

The docking poses were ranked according to their docking scores, and both the ranked list of docked ligands and their corresponding binding poses ²⁷. In Fig3, the docked pose of aldosereductase enzyme with Avicularin clearly demonstrates the binding positions of the ligand with the enzyme. Binding energy of the lead molecule was calculated using the following formula:

Binding energy = A+B+C-D

Where, A denotes final intermolecular energy + van der Walls energy (vdW) + hydrogen bonds + desolvation energy + electrostatic energy (kcal/mol), B denotes final total internal energy (kcal/mol), C denotes torsional free energy (kcal/mol), D denotes the unbound system’s energy (kcal/mol). Analysis of the receptor/ligand complex models generated after successful docking of the lead molecule, based on parameters such as hydrogen bond interactions ^{28, 29}. As a general rule, in most of the potent lead molecules, both hydrogen bonding and hydrophobic interactions between the lead molecule and the active sites of the receptor have been found to be responsible for mediating the biologicalactivity.

CONCLUSION:

In conclusion, the data obtained from the in silico studies evidenced the regulatory role of Avicularin in the regulation of glucose homeostasis, and further studies are in progress to elucidate the interaction between Avicularin and other relevant targets to substantiate its role in eliciting significant antidiabetic activity.

CONFLICT OF INTEREST:

The authors declare that there is no conflict of interest.

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Received on 05.05.2023 Modified on 15.09.2023

Research J. Pharm. and Tech 2024; 17(1):19-24.

DOI: 10.52711/0974-360X.2024.00004